Background Heart disease remains the leading cause of death in the United States. Although there are clear indications for revascularization in patients with acute coronary syndromes, there is debate regarding the benefits of revascularization in stable ischemic heart disease. We sought to perform a comprehensive meta‐analysis to assess the role of revascularization compared to conservative medical therapy alone in patients with stable ischemic heart disease. Hypothesis There is no significant difference in all‐cause mortality or cardiovascular mortality between invasive and medical arms. Methods We performed a systematic literature search from January 2000 to June 2020. Our literature search yielded seven randomized controlled trials. We analyzed a total of 12 013 patients (6109 in revascularization arm and 5904 in conservative medical therapy arm). Primary outcome was all‐cause mortality. Secondary outcomes included major adverse cardiac events (MACE) (death, myocardial infarction [MI], or stroke), cardiovascular mortality, MI, and stroke. Additional subgroup analysis for all‐cause mortality was performed comparing percutaneous coronary intervention (PCI) with bare metal stent versus conservative therapy; and PCI with drug eluting stent versus conservative therapy. Results There was no statistically significant difference in primary outcome of all‐cause mortality between either arm (odds ratio [OR] = 0.95; 95% CI [confidence interval], 0.83 to 1.08; p = .84). There were statistically significant lower rates of MACE (death, MI or stroke) in the revascularization arm when compared to conservative arm. Conclusions Our analysis did not show any survival advantage of an initial invasive strategy over conservative medical therapy in patients with stable coronary artery disease (CAD).

Motorcycle crashes and fatalities remain a significant public health problem as fatality rates have increased substantially as compared to other vehicle types in the United States. Analysis of causal factors for motorcycle crashes is often challenging given a lack of reliable traffic volume data and the fact that such crashes comprise a relatively small portion of all traffic crashes. Given these limitations, on-scene crash investigations represent an ideal setting through which to investigate the precipitating factors for motorcycle-involved crashes. This study examines motorcycle crash risk factors by employing data recently made available from the Federal Highway Administration Motorcycle Crash Causation Study (MCCS). The MCCS represents a comprehensive investigative effort to determine the causes of motorcycle crashes and involved the collection of in-depth data from 351 crashes, as well as the collection of comparison data from 702 paired control observations in Orange County, California. This dataset provides a unique opportunity to understand how the risk of crash involvement varies across different segments of the riding population. Logistic regression models are estimated to identify the rider and vehicle attributes associated with motorcycle crashes. The results of the study suggest that motorcycle crash risks are related to rider age, physical status, and educational attainment. In addition to such factors outside of the rider’s control, several modifiable risk factors, which arguably affect the riders’ proclivity to take risks, were also found to be significantly associated with motorcycle crash risk, including motorcycle type, helmet coverage, motorcycle ownership, speed, trip destination, and traffic violation history.

The relationship between traffic safety and speed limits has been an area of significant research. Since the repeal of the National Maximum Speed Law in 1995, states have full autonomy in establishing maximum statutory speed limits. Since 2001, at least 25 states have increased their maximum limits to speeds as high as 85 mph. This study examines changes in rural interstate fatalities from 2001 to 2016 in consideration of such increases. Speed limit policy data include the maximum speed limit for each state–year combination, as well as the proportion of rural interstate mileage posted at each speed limit in each state. Random parameter negative binomial models are estimated to control for unobserved heterogeneity, as well as time-invariant effects unique to each state. The results show that increasing the mileage of rural interstates posted at 70, 75, or 80 mph by 1% is associated with fatality increases of 0.2%, 0.5%, and 0.6%, respectively. These increases are more pronounced than when considering only the maximum statutory limits in each state. The study also examines the influence between these higher limits and the frequency of fatal crashes involving speeding and driver distraction. At the highest limits of 75 and 80 mph, the increases among these subsets of crashes are greater than the increases in total fatalities. Ultimately, this study provides important empirical evidence in support of continuing speed limit policy discussions, in addition to identifying salient analytical concerns that should be considered as a part of longitudinal analyses of state-level fatality data.

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